Introduction

This study is an exciting topic regarding UW courses and potentially could reach a lot of student’s demographics. A lot of students go to sites like ratemyprofessor.com or UW’s course evaluation to learn more about the courses before they commit. Therefore, the scarcity of the information circulating leads to considerable demand for such insights. By visualizing the avg GPA of UW courses, students can better assess the difficulties of each class they are taking. It also helps to foster transparency across college courses and would help us to make informed decisions to choose the right schedule for us.

Summary

Table

For the summary table, we choose to summarize the dataset by the popularity of classes. The popularity of class will be based on the student count of individual class. The most popular class will be the class with the largest student count number. We want to use this table to provide a insight of enrollment statistics of each informatics classes and student’s preferences among these classes. As indicated in the table, the most popular class is INFO 200 INTELL FOUNDATIONS which has a total student enrollment of 6678. The least popular class is INFO 245: DB MGMT FNDMNTLS II which only has a total student enrollment of 18.

course_tag course_title class_popularity
INFO 200 INTELL FOUNDATIONS 6678
INFO 101 SOCIAL NETWORKING 3013
INFO 490 CAPSTONE PROJECT I 2632
INFO 360 DESIGN THINKING 2390
INFO 498 TOPIC INFORMATICS 2138
INFO 470 RES METHODS IN INFO 1869
INFO 450 INFO ETHICS & POLCY 1792
INFO 481 PROJECT MANAGEMENT 1716
INFO 340 RELATNL DB MGMT SYS 1550
INFO 201 TECH FOUNDATIONS 1547
INFO 343 CLIENT-SIDE WEB DEV 1517
INFO 102 GENDER & INFO TECH 1221
INFO 491 CAPSTONE PROJECT II 1095
INFO 380 IS ANALYSIS & DSGN 850
INFO 445 ADV DBMS DESIGN 768
INFO 330 UX & INFO ARCH 703
INFO 330 INFO STUCTURES 664
INFO 341 COMP NET & DIST APP 603
INFO 340 DBM & INFO RET SYS 601
INFO 344 SERVER-SIDE WEB DEV 540
INFO 386 PROFESSIONALISM 534
INFO 424 INFO VIS & AESTH 504
INFO 370 INTRO DATA SCIENCE 501
INFO 343 WEB TECHNOLOGIES 488
INFO 362 VISUAL INFO DESIGN 482
INFO 380 IS ANALYSIS & MGMT 474
INFO 310 INFO ASSR & CYBRSEC 459
INFO 466 IMMERSIVE ENVIRMNTS 452
INFO 100 COMPUTER FLUENCY 422
INFO 360 DESIGN METHODS 366
INFO 344 WEB TOOLS & DEV 298
INFO 312 ENTRPRISE RISK MGMT 275
INFO 474 INTERACTIVE INFO VIS 271
INFO 270 DATA RSNG DIGIT WRLD 262
INFO 198 EXPLORING INFORM 256
INFO 415 TOPICS IN CYBERSEC 243
INFO 300 RESEARCH METHODS 227
INFO 433 CONTENT STRATEGY 214
INFO 463 INPUT & INTERACTION 212
INFO 448 ANDROID MOBILE DEV 206
INFO 490 DSGN DEV INTER SYS 204
INFO 371 DATA SCIENCE METHDS 189
INFO 444 VAL SEN DESIGN 178
INFO 320 INFO NEEDS SRCHING 169
INFO 340 CLIENT-SIDE DEV 151
INFO 461 COOP SOFTWARE DSGN 150
INFO 449 IOS MOBILE DEV 144
INFO 330 DB & DATA MODELING 143
INFO 180 INTRO DATA SCIENCE 132
INFO 365 MOBILE APP DESIGN 110
INFO 447 COMP SUPP COOP WRK 109
INFO 467 IMMERSIVE ENVIR DSN 108
INFO 370 DATA SCIENCE METHDS 102
INFO 102 WOMEN IN TECHNOLOGY 94
INFO 360 USER-CTR DESIGN 77
INFO 431 METADATA DESIGN 77
INFO 402 GENDER, EQUITY & IT 64
INFO 310 IAC FOUNDATIONS 37
INFO 240 DB MGMT FNDMNTLS I 34
INFO 430 DB DESIGN & MGMT 34
INFO 461 COOPERTIV USR-CNTR 26
INFO 441 SERVER-SIDE DEV 22
INFO 245 DB MGMT FNDMNTLS II 18

Charts

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Chart 2 - Average GPAs for INFO courses

Next we want to include a high-level overview of students’ performance on all the 100 - 400 level INFO courses from 2010 autumn to 2018 autumn. We first define “students’ performance” to be the average GPA score, since the mean value is a good indicator of performance here, and since we have access to the average GPA data for each INFO course at each its operating quarter and year, so we can easily compute the final average GPA score of each course for all its operating quarters. We then chose the scatterplot as our visualization tool for the aforementioned aim, since each data point we want to plot, which is the average GPA for the according course, can be easily represented by a circle/marker. And after placing all the markers on a scatterplot, we are able to see the change of performance as the course level proceeds. Another important motive is we also want to give the readers an insight of the average size of each course, and this can be easily accomplished by just decr/increasing the radius of each marker!

From the chart, we observed that intro courses generally have a bigger class size. In specific, INFO 100, 101, 102, 198, 200, 201, 270, 300 are significant in their class size. For the courses in the middle i.e. intermediate level courses, class sizes are getting much smaller to around 30 except for INFO 380, with two different titles, which had an average class size of approximately 120. Lastly for the upper division courses, their size are kept small to around 30 as well but with a few more exceptions: INFO 450, 470, 490, 491, which have an average class size ranging from 68 to all the way to 139. The average GPAs for INFO courses are between 3.3 to 3.9, where the least value is held by INFO 180, 344, 447, 461 and the most is held by INFO 365 and 491.

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Chart 3 - GPA distribution across info200 class

This graph shows the gpa distribution of each letter grades from all professors of the class. The reason to include this graph is that it explains the grading disparity across sections. For example, the majority of the Chapin’s class earned A, while very few students from Freeman’s class earned an A. Using stacked bar chart we can clearly see some professor gives eaiser grades on the class, while others are tougher. There is no other graph can present this information clearly.

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